Abstract

Background

Recent in vivo studies showed new hopes of drug repositioning through causality inference from drugs
to disease. Inspired by their success, here we present an in silico method for building a causal network (CauseNet) between drugs and diseases, in an
attempt to systematically identify new therapeutic uses of existing drugs.

Results

To demonstrate its validity, our method showed high performance (AUC = 0.859) in cross
validation. Moreover, our top scored prediction results are highly enriched in literature
and clinical trials. As a showcase of its utility, we show several drugs for potential
re-use in Crohn's Disease.

Conclusions

We successfully developed a computational method for discovering new uses of existing
drugs based on casual inference in a layered drug-target-pathway-gene- disease network.
The results showed that our proposed method enables hypothesis generation from public
accessible biological data for drug repositioning.